code: def test_remove_by_feature_importance(logs):
      log = first(logs)
      next_features = remove_by_feature_importance(
          log, num_removed_by_step=2
      )
      assert next_features == ["x1", "x3", "x5"]
  
file_path: fklearn/tests/tuning/test_samplers.py
imports: import pandas
  import pytest
  from tests import LOGS, PARALLEL_LOGS
  from toolz.curried import first
  from fklearn.metrics.pd_extractors import evaluator_extractor
  from fklearn.training.classification import logistic_classification_learner
  from fklearn.tuning.samplers import remove_by_feature_importance, remove_by_feature_shuffling, remove_features_subsets
  from fklearn.validation.evaluators import roc_auc_evaluator
label_desc: Use image node_id 9 for calling a global function with example usage: test_remove_by_feature_importance(logs) without return types